Journal article
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
British journal of surgery, Vol.108(11), pp.1274-1292
11/11/2021
DOI: 10.1093/bjs/znab183
PMCID: PMC8344569
PMID: 34227657
Abstract
To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
Details
- Title: Subtitle
- Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
- Creators
- COVIDSurg CollaborativeLaura BravoDmitri Nepogodiev - University of BirminghamJames C. Glasbey - University of BristolElizabeth LiA F Utria (Contributor)
- Resource Type
- Journal article
- Publication Details
- British journal of surgery, Vol.108(11), pp.1274-1292
- DOI
- 10.1093/bjs/znab183
- PMID
- 34227657
- PMCID
- PMC8344569
- NLM abbreviation
- Br J Surg
- ISSN
- 0007-1323
- eISSN
- 1365-2168
- Publisher
- Wiley
- Number of pages
- 19
- Language
- English
- Date published
- 11/11/2021
- Academic Unit
- Surgery
- Record Identifier
- 9985015820502771
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